Results 21 to 30 of about 211,231 (266)
Review of Deep Learning Applied to Occluded Object Detection [PDF]
Jisuanji kexue yu tansuo, 2022 Occluded object detection has long been a difficulty and hot topic in the field of computer vision. Based on convolutional neural network, the deep learning takes the object detection task as a classification and regression task to handle, and obtains ...
SUN Fangwei, LI Chengyang, XIE Yongqiang, LI Zhongbo, YANG Caidong, QI Jin
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A Two-Phase Super-Resolution Quantization Scheme Optimized by Sequential Grading and Data Bias Correction [PDF]
Jisuanji gongchengModel quantization technology effectively reduces model storage and computational overhead by mapping high-precision floating-point data to low-bit discrete spaces.
HAO Liang, SU Bohejun, WANG Jinghua, XU Yong
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Object detection grammars [PDF]
2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011 In this talk I will discuss various aspects of object detection using compositional models, focusing on the framework of object detection grammars, discriminative training and efficient computation.
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Described Object Detection: Liberating Object Detection with Flexible Expressions
Advances in Neural Information Processing Systems 36, 2023 Detecting objects based on language information is a popular task that includes Open-Vocabulary object Detection (OVD) and Referring Expression Comprehension (REC). In this paper, we advance them to a more practical setting called Described Object Detection (DOD) by expanding category names to flexible language expressions for OVD and overcoming the ...
Chi Xie +5 more
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Video Object Detection Guided by Object Blur Evaluation
IEEE Access, 2020 In recent years, the excellent image-based object detection algorithms are transferred to the video object detection directly. These frame-by-frame processing methods are suboptimal owing to the degenerate object appearance such as motion blur, defocus ...
Yujie Wu +4 more
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RecFRCN: Few-Shot Object Detection With Recalibrated Faster R-CNN
IEEE Access, 2023 Currently, Faster R-CNN serves as the fundamental detection framework in the majority of few-shot object detection algorithms. However, due to limited samples per class, the Faster R-CNN’s classification branch faces limitations in capturing ...
Youyou Zhang, Tongwei Lu
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Anchor pruning for object detection
Computer Vision and Image Understanding, 2022 This paper proposes anchor pruning for object detection in one-stage anchor-based detectors. While pruning techniques are widely used to reduce the computational cost of convolutional neural networks, they tend to focus on optimizing the backbone networks where often most computations are.
Maxim Bonnaerens +2 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 RGB–infrared object detection in remote-sensing images is crucial for achieving around-clock surveillance of unmanned aerial vehicles.
Jin Xie +4 more
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YOLOv7-3D: A Monocular 3D Traffic Object Detection Method from a Roadside Perspective
Applied Sciences, 2023 Current autonomous driving systems predominantly focus on 3D object perception from the vehicle’s perspective. However, the single-camera 3D object detection algorithm in the roadside monitoring scenario provides stereo perception of traffic objects ...
Zixun Ye +3 more
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Fast Recognition and Counting Method of Dragon Fruit Flowers and Fruits Based on Video Stream
Sensors, 2023 Dragon fruit (Hylocereus undatus) is a tropical and subtropical fruit that undergoes multiple ripening cycles throughout the year. Accurate monitoring of the flower and fruit quantities at various stages is crucial for growers to estimate yields, plan ...
Xiuhua Li +5 more
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